Generally, the more textured or complex the video content is, the more artifacts in the video content can be tolerated by human eyes. That is, when a video content is viewed by human eyes, visual artifacts may be masked by the video content itself. This property of human eyes is known as masking property or masking effect. Thus, content complexity may be considered in visual quality assessment.
In our previous work, we estimate a content unpredictability (CU) parameter to indicate content complexity. In a commonly owned PCT application, entitled “Method and apparatus for video quality measurement” by F. Zhang, N. Liao, K. Xie, and Z. Chen (PCT/CN11/002096, hereinafter “Zhang1”), the teachings of which are specifically incorporated herein by reference, we disclosed a method for predicting video quality using a quantization parameter (QP), which is adjusted by a correction function that depends on content unpredictability.
In another commonly owned PCT application, entitled “Video quality measurement” by F. Zhang, N. Liao, K. Xie, and Z. Chen (PCT/CN2011/082870, hereinafter “Zhang2”), the teachings of which are specifically incorporated herein by reference, we disclosed a method for estimating a compression distortion factor, a slicing distortion factor, and a freezing distortion factor using parameters (for example, quantization parameters, content unpredictability parameters, ratios of lost blocks, ratios of propagated blocks, error concealment distances, motion vectors, durations of freezing, and frame rates) derived from a bitstream.